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In this study, a highly crystalline and transparent indium-tin-oxide (ITO) thin film was prepared on a quartz substrate via RF sputtering to fabricate an efficient bottom-to-top illuminated electrode for an ultraviolet C (UVC) photodetector. Accordingly, the 26.6 nm thick ITO thin film, which was deposited using the sputtering method followed by post-annealing treatment, exhibited good transparency to deep-UV spectra (67% at a wavelength of 254 nm), along with high electrical conductivity (11.3 S/cm). Under 254 nm UVC illumination, the lead-halide-perovskite-based photodetector developed on the prepared ITO electrode in a vertical structure exhibited an excellent on/off ratio of 1.05 × 104, a superb responsivity of 250.98 mA/W, and a high specific detectivity of 4.71 × 1012 Jones without external energy consumption. This study indicates that post-annealed ITO ultrathin films can be used as electrodes that satisfy both the electrical conductivity and deep-UV transparency requirements for high-performance bottom-illuminated optoelectronic devices, particularly for use in UVC photodetectors.

Abstract Sunlight‐originated ultraviolet B (UVB) rays influence daily life in both beneficial and detrimental ways, depending upon light power and exposure time. Therefore, precise and timely UVB irradiance control is of great importance to humans. This study proposes a self‐powered and wearable zinc sulfide (ZnS) nanoparticle (NP)‐based UVB‐C detector for the in situ monitoring of UVB levels in ambient environments. The performance of the ZnS‐based photodetector can be markedly enhanced by constructing a vertical p‐n heterojunction for testing the feasibility of a self‐powered UVB‐C detector, employing a thin polyethylenimine (PEI) film for inhibiting current leakage and charge recombination, and introducing a poly(9,9‐dioctylfluorene‐alt‐N‐[4‐s‐butylphenyl]‐diphenylamine) (TFB) film as a hole transport layer to increase the photocurrent and enhance the response speed. In particular, we demonstrate that the ZnS NP/TFB junction in the device enables the direct monitoring of narrow and specific UVB bands from sunlight owing to its unique energy band structure and light absorption characteristics. The optimized device has a fast rise/fall time of 50/62 ms, high specific detectivity of 8.20 × 1010 Jones, and good stability over long‐term storage and against mechanical bending under 254‐nm light illumination. Our study provides new insights into self‐powered devices that can be implemented for the facile, precise, and rapid estimation of UVB levels under sunlight for various personal healthcare applications.

Recommendation systems based on convolutional neural network (CNN) have attracted great attention due to their effectiveness in processing unstructured data such as images or audio. However, a huge amount of raw data produced by data crawling and digital transformation is structured, which makes it difficult to utilize the advantages of CNN. This paper introduces a novel autoencoder, named Half Convolutional Autoencoder, which adopts convolutional layers to discover the high-order correlation between structured features in the form of Tag Genome, the side information associated with each movie in the MovieLens 20 M dataset, in order to generate a robust feature vector. Subsequently, these new movie representations, along with the introduction of users’ characteristics generated via Tag Genome and their past transactions, are applied into well-known matrix factorization models to resolve the initialization problem and enhance the predicting results. This method not only outperforms traditional matrix factorization techniques by at least 5.35% in terms of accuracy but also stabilizes the training process and guarantees faster convergence.

This paper considers a non-orthogonal multiple access (NOMA) multi-user relay system where both source and relay harvest the energy from a power beacon (PB) equipped with multiple antennas and use this harvested energy to transmit signals to several users. Realistic nonlinear energy harvesting models are applied, and time switching protocols are adopted at source and relay. We successfully derive the exact closed-form expressions of the outage probability and throughput of the system over Nakagami- m fading channels. Then, we use Monte-Carlo simulations to validate the correctness of these derived mathematical expressions. Numerical results show that a higher saturated power threshold of the nonlinear energy harvester results in lower outage probability and higher throughput. Moreover, the optimal time switching ratio that maximizes the throughput is smaller than the optimal time switching ratio that minimizes the outage probability., Competing Interests: The authors declare no conflict of interest., (© 2020 Published by Elsevier Ltd.)

In this paper, we propose, implement, and analyze the structures of two keyed hash functions using the Chaotic Neural Network (CNN). These structures are based on Sponge construction, and they produce two variants of hash value lengths, i.e., 256 and 512 bits. The first structure is composed of two-layered CNN, while the second one is formed by one-layered CNN and a combination of nonlinear functions. Indeed, the proposed structures employ two strong nonlinear systems, precisely a chaotic system and a neural network system. In addition, the proposed study is a new methodology of combining chaotic neural networks and Sponge construction that is proved secure against known attacks. The performance of the two proposed structures is analyzed in terms of security and speed. For the security measures, the number of hits of the two proposed structures doesn't exceed 2 for 256-bit hash values and does not exceed 3 for 512-bit hash values. In terms of speed, the average number of cycles to hash one data byte (NCpB) is equal to 50.30 for Structure 1, and 21.21 and 24.56 for Structure 2 with 8 and 24 rounds, respectively. In addition, the performance of the two proposed structures is compared with that of the standard hash functions SHA-3, SHA-2, and with other classical chaos-based hash functions in the literature. The results of cryptanalytic analysis and the statistical tests highlight the robustness of the proposed keyed hash functions. It also shows the suitability of the proposed hash functions for the application such as Message Authentication, Data Integrity, Digital Signature, and Authenticated Encryption with Associated Data.

A downlink of multi-user non-orthogonal multiple access (NOMA) relay systems is considered. To improve system performance, relay nodes are used to forward signals from the base station (BS) to the end users, and they are wirelessly powered by energy harvesting from the radio frequency transmitted from the BS. Moreover, beamforming is applied at the BS based on multiple antennas and relay nodes consist of one transmit antenna but several receive ones. The system performance is demonstrated through closed-form expressions of outage probability (OP) and ergodic rate (ER) over Rayleigh fading channels. The proposed system is investigated in two cases of perfect and imperfect successive interference cancellation (SIC), and the imperfect channel state information condition is also taken into consideration. The OP and ER are calculated in many scenarios and the optimal time fraction of energy harvesting corresponding to the minimum OP is discussed. The exact and approximate theoretical results are compared with the simulation result to confirm the proposed theoretical analysis method., Competing Interests: The authors declare no conflicts of interest.